Pt Catalysts Supported on H<sub>2</sub> and O<sub>2</sub> Plasma-Treated Al<sub>2</sub>O<sub>3</sub> for Hydrogenation and Dehydrogenation of the Liquid Organic Hydrogen Carrier Pair Dibenzyltoluene and Perhydrodibenzyltoluene
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Dibenzyltoluene (DBT) is a promising liquid organic hydrogen carrier (LOHC) with theoretical 6.2 wt % hydrogen storage capacity which can be coupled with a renewable energy power generation system. In this work, the surface hydroxyl groups and surface oxygen vacancies (SOVs) on alumina were modified by a convenient and environmentally friendly plasma treatment method. Different Pt/Al2O3 catalysts were prepared via impregnation of the treated alumina, and the effects of different surface hydroxyl groups and SOVs on their reactivity for the reversible hydrogenation and dehydrogenation of DBT were investigated. The results show that SOVs increased after H2 plasma treatment, whereas the surface hydroxyl groups increased and SOVs decreased after O2 plasma treatment. Both the surface hydroxyl group and SOV can improve Pt metal dispersion. The more interesting observation is that the hydroxyl groups promote hydrogen spillover and the proportion of Pt(0), which not only benefit the catalyst hydrogenation and dehydrogenation activity but also reduce side reactions and increase long-term cycle performance. However, increased SOVs increased the fraction of low coordinated Pt which reduces the long-term cycle performance of the catalyst. As a result, increasing surface hydroxyl groups and appropriately reducing SOVs on Pt/Al2O3 are propitious for improving both reactivity and long-term cycle performance when using DBT as a LOHC.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it